Xiao et al. [1]} introduced the first person search dataset, i.e., CUHK-SYSU, collected from street snaps and movie/TV frames. PRW [2]} is a collection of images from surveillance videos. These two existing datasets have been used to evaluate methods for searching persons in different places. In the era of social media and big data, there is an increasing need for searching persons on the Internet, especially movie stars and political celebrities. However, a big gap between searching the person on the street and retrieving a person from the Internet is that the clothing of the target person usually changes across different scenes. To be more specific, a movie cast tends to wear different clothes in different movies or even a single movie. In such cases, the clothing is not a reliable basis of distinction any more. Furthermore, if criminals may change their clothes in different zones, the existing hypothetical basis of normal person re-ID is not established. Given the above facts and observations, it is important to make an exploration on pushing the normal person re-ID and person search into a more general task, which is the character re-identification and character search, respectively. The well-behaved character search could bring more convenient entertaining and safer living for our daily life. In [3]}, Huang et al. proposed a holistic dataset for movie understanding, where rich annotations for character detection and character identification have been provided. Owing to this great work, an apposite dataset and a baseline method for character identification have been given, which provides a great chance to extend the character identification to character search, which is much more in line with practical applications.
